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How to Check Column Nulls and Replace: Pandas

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Here is a post that shows how to count Nulls and replace them with the value you want in the Pandas Dataframe. We have explained the process in two steps - Counting and Replacing the Null values. Count null values (column-wise) in Pandas ## count null values column-wise null_counts = df.isnull(). sum() print(null_counts) ``` Output: ``` Column1    1 Column2    1 Column3    5 dtype: int64 ``` In the above code, we first create a sample Pandas DataFrame `df` with some null values. Then, we use the `isnull()` function to create a DataFrame of the same shape as `df`, where each element is a boolean value indicating whether that element is null or not. Finally, we use the `sum()` function to count the number of null values in each column of the resulting DataFrame. The output shows the count of null values column-wise. to count null values column-wise: ``` df.isnull().sum() ``` ##Code snippet to count null values row-wise: ``` df.isnull().sum(axis=1) ``` In the above code, `df` is the Panda

Python Delete Duplicates in List Faster Way

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Removing duplicates in List simplified using SET method. It's a simple method. Just you need SET and Print to remove duplicates. Removing duplicates is common in Data science projects. What is list A list is a collection of elements. The elements can be duplicates or non-duplicates. Today's task is to remove duplicate elements in the List. Faster way to remove list duplicates Create a List Use SET Print the result List with duplicates my_list = ['The', 'unanimous', 'Declaration', 'of', 'the', 'thirteen','united', 'States', 'of', 'America,', 'When', 'in', 'the', 'Course', 'of', 'human'] Apply set method >>> non_dupes = set(my_list) Print Final list >>> print(non_dupes) Here, if you observe, there are no duplicates. The duplicates are now removed. It displays only non-duplicate values.  Here 'the' is a duplicate value. That'